De Matas, Marcel, Shao, Qun, Biddiscombe, Martyn F., Meah, Sally, Chrystyn, Henry and Usmani, Omar S. (2010) Predicting the clinical effect of a short acting bronchodilator in individual patients using artificial neural networks. European Journal of Pharmaceutical Sciences, 41 (5). pp. 707-715. ISSN 0928-0987

Artificial neural networks were used in this study to model the relationships between in vitro data, subject characteristics and in vivo outcomes from N = 18 mild–moderate asthmatics receiving monodisperse salbutamol sulphate aerosols of 1.5, 3 and 6 μm mass median aerodynamic diameter in a cumulative dosing schedule of 10, 20, 40 and 100 μg. Input variables to the model were aerodynamic particle size (APS), body surface area (BSA), age, pre-treatment forced expiratory volume in one-second (FEV1), forced vital capacity, cumulative emitted drug dose and bronchodilator reversibility to a standard salbutamol sulphate 200 μg dose MDI (REV(%)). These factors were used by the model to predict the bronchodilator response at 10 (T10) and 20 (T20) min after receiving each of the 4 doses for each of the 3 different particle sizes. Predictability was assessed using data from selected patients in this study, which were set aside and not used in model generation. Models reliably predicted ΔFEV1(%) in individual subjects with non-linear determinants (R2) of ≥0.8. The average error between predicted and observed ΔFEV1(%) for individual subjects was <4% across the cumulative dosing regimen. Increases in APS and drug dose gave improved ΔFEV1(%). Models also showed trends towards improved responses in younger patients and those having greater REV(%), whilst BSA was also shown to influence clinical effect. These data show that APS can be used to discriminate predictably between aerosols giving different bronchodilator responses across a cumulative dosing schedule, whilst patient characteristics can be used to reliably estimate clinical response in individual subjects.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email